Gene expression analysis is a technique that evaluates the expression of the transcriptional gene in the coding region of a specific genome. Gene expression analysis quantifies the expression of genes by assessing mRNA, detects gene fusions, identifies novel and known isoforms of the coding transcriptome, and measures allele-specific expression.
Like complex methodologies such as immunogenicity assay, copy number variation assay, and ddPCR services, gene expression analysis can help study underlying pathological pathways and influence the molecular basis of diseases. Copy number analysis, often called copy number qPCR assays, analyzes copy number variation in an organism’s DNA. Such specific gene testing approaches are critical in biomedical and clinical studies. The current article discusses the process of gene expression analysis to understand the molecular basis behind diseases and disorders.
Gene expression analysis: deciphering molecular mechanisms of diseases
Depending on the study’s end goals, multiple methods are available to analyze gene expression for selected targets and coding transcriptome. These methods include next-generation sequencing, qRT-PCR analysis, gene expression, microarrays, etc. Each of these methods has unique applications and considerations.
Let us explore these Gene Expression Analysis methods in disease biology.
Next-generation RNA sequencing
This approach can detect novel and known elements in a single assay run. It provides a broader dynamic range and can be considered for any species. Importantly, it is cost-effective and scalable for high throughput analysis. The primary consideration is that sequencing targets present in low numbers can be time-consuming.
Gene expression microarrays
Gene expression microarrays have similar workflows and offer high sample throughput for assessing known transcripts and genes. However, gene expression microarrays cannot identify novel transcripts. This method is limited by signal saturation at the higher degree, while background noise is at the lower end.
qRT-PCR analysis
qRT-PCR has a simple and rapid workflow and uses instruments already available in most laboratories. Besides, it is effective in analyzing low target numbers. However, the primary consideration in qRT-PCR is that it offers no scalability and detects only known sequences.
Large-scale studies of proteins and genes are called proteomics and genomics, respectively. Today, scientists use gene chips to study mRNA levels of human protein and coding genes in a specific cell population. Gene chips are like single nucleotide polymorphism chips. However, gene chips have grids containing single-stranded DNA corresponding to proteins in coding genes.
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To assess gene expression using gene chips, researchers isolate messenger RNA from target tissue, convert it into cyclic DNA, and label it with a fluorescent dye. This fluorescently labeled cyclic DNA is incubated in a gene chip and allowed to hybridize with their complementary sequences. A laser then scans the gene chip and determines the generated signal for each mRNA to yield the expression profile for the gene of interest. Scientists compare the gene expression levels of a normal cell with a diseased cell to identify the changes in gene expression and associate it with the disease of interest.
In Conclusion
Ever-increasing data on gene expression and the advent of novel molecular technology in gene discovery and evaluations have greatly expanded our understanding of disease mechanisms and underlying biology.
